Safety and Efficacy of Adult Stem Cell Therapy for Acute Myocardial Infarction and Ischemic Heart Failure (SafeCell Heart): A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Preclinical and clinical evidence suggests that mesenchymal stem cells (MSCs) may be beneficial in treating both acute myocardial infarction (AMI) and ischemic heart failure (IHF). However, the safety profile and efficacy of MSC therapy is not well-known. We conducted a systematic review of clinical trials that evaluated the safety or efficacy of MSCs for AMI or IHF. Embase, PubMed/Medline, and Cochrane Central Register of Controlled Trials were searched from inception to September 27, 2017. Studies that examined the use of MSCs administered to adults with AMI or IHF were eligible. The Cochrane risk of bias tool was used to assess bias of included studies. The primary outcome was safety assessed by adverse events and the secondary outcome was efficacy which was assessed by mortality and left ventricular ejection fraction (LVEF). A total of 668 citations were reviewed and 23 studies met eligibility criteria. Of these, 11 studies evaluated AMI and 12 studies evaluated IHF. There was no association between MSCs and acute adverse events. There was a significant improvement in overall LVEF in patients who received MSCs (SMD 0.73, 95% CI 0.24-1.21). No significant difference in mortality was noted (Peto OR 0.68, 95% CI 0.38-1.22). Results from our systematic review suggest that MSC therapy for ischemic heart disease appears to be safe. There is a need for a well-designed adequately powered randomized control trial (with rigorous adverse event reporting and evaluations of cardiac function) to further establish a clear risk-benefit profile of MSCs. Stem Cells Translational Medicine 2018;7:857-866.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.031 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".